It has been the seventh International Workshop on Climate Informatics and we believe it had much success in accelerating discovery at the intersection of these disciplines. For the 2017 workshop, participants convened at the National Center for Atmospheric Research (NCAR) in Boulder, Colorado between September 20-22. The main workshop (September 21-22) featured five invited speakers, a poster session, short talks by several early career scientists, and two panel discussions. Invited speakers covered many topics from across the spectrum of climate informatics: Alexis Hannart (Ouranos) explained how causal counterfactual theory can be used to attribute events in the climate system; Robert Lund (Clemson University) spoke about statistical challenges posed by analyzing trends in real-world observations; Elisabeth Moyer (University of Chicago) explained how climate models can be most efficiently used to augment limited observations; Prabhat (Lawrence Berkeley National Laboratory) presented recent advances in using deep learning at scale to identify extreme events such as hurricanes and atmospheric rivers; and Sai Ravela (MIT) described how physical constraints can be used to improve machine learning in the context of data assimilation systems.
